Michael Buckley - SEALS - Whole Exome Sequencing in the Clinic
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Michael Buckley - SEALS - Whole Exome Sequencing in the Clinic

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Associate Professor Michael Buckley, Clinical Director and Senior Staff Specialist, SEALS presented "Whole Exome Sequencing in the Clinic" at the National Pathology Forum 2013. ...

Associate Professor Michael Buckley, Clinical Director and Senior Staff Specialist, SEALS presented "Whole Exome Sequencing in the Clinic" at the National Pathology Forum 2013.

This annual conference provides a platform for the public and private sectors to come together and discuss all the latest issues affecting the pathology sector in Australia. For more information, please visit the conference website: http://www.informa.com.au/pathologyforum

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Michael Buckley - SEALS - Whole Exome Sequencing in the Clinic Presentation Transcript

  • 1. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Exome Sequencing in the Clinic Michael Buckley Clinical Director, S.E.A.L.S. Genetics Laboratory Randwick Hospitals Campus, Sydney School of Medical Sciences, UNSW
  • 2. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics A Quick Orientation CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 3. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics A Quick Orientation • Humans have 46 chromosomes, 22 autosomal pairs and 1 sex chr pair • Everyone has ~6,000,000,000 base pairs of DNA in each nucleated cell • Genome = condensation of the words ‘Gene and Chromosome’ CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 4. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Transcribed and protein-coding regions • There is good evidence for 20,687 protein coding genes and a further 11,224 pseudogenes • On average, each gene produces 4 alternately spliced mRNA transcripts CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 5. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Transcribed and protein-coding regions • There is good evidence for 20,687 protein coding genes and a further 11,224 pseudogenes • On average, each gene produces 4 alternately spliced mRNA transcripts • Protein coding genes span 33.45% of the genome from outermost start to stop codons; 39.54% from promotor to poly(A) • But protein coding and non-coding exons cover 2.94% of genome; purely protein coding exons account for 1.22% for protein coding exons CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 6. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Transcribed and protein-coding regions • There is good evidence for 20,687 protein coding genes and a further 11,224 pseudogenes • On average, each gene produces 4 alternately spliced mRNA transcripts • Protein coding genes span 33.45% from outermost start to stop codons; 39.54% from promotor to poly(A) • Both protein coding and non-coding exons cover 2.94% of genome; purely protein coding exons account for 1.22% for protein coding exons • 70,292 with promotor-like features that turn gene expression on and off • There are 399,124 regions with enhancer-like features which help regulate expression levels CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 7. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Genome Methylome CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 8. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics DNA methylation • Methylation of cytosine (especially at CpG dinucleotides) involved in (epigenetic) regulation of gene expression • 96% of CpGs exhibited differential methylation in at least one cell type or tissue • Levels of DNA methylation correlated with chromatin accessibility • Gene promotor methylation is generally associated with repression • Reproducible cytosine methylation seen outside CpG dinucleotides; may have important roles in human biology CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 9. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Genome Methylome Transcription Transcriptome CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 10. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Most of the Genome is Functional • 80.4% of genome “participates in at least one biochemical RNAand/or chromatin-associated event in at least one cell type” • 95% of genome lies within 8kb of a DNA-protein interaction • 99% is within 1kb of at least one of the biochemical event CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 11. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Genome Methylome Transcription Transcriptome Translation Proteome Small RNAome CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 12. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Inherited & essentially same in all nuclei Genome Methylome Transcription Transcriptome Translation Proteome Small RNAome CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 13. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Inherited & essentially same in all nuclei Genome Methylome Transcription Transcriptome Cell/tissue specific Translation Proteome Small RNAome CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 14. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics The Exome • The exome is the part of the genome formed by exons, the sequences which when transcribed remain within the mature RNA after introns are removed by RNA splicing • There are ~180-200,000 coding exons in the human genome • Represents approximately 30 Mb of the total 6.4Gb diploid human genome (~1.1% of the total) CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 15. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics The Exome • The exome is the part of the genome formed by exons, the sequences which when transcribed remain within the mature RNA after introns are removed by RNA splicing • There are ~180-200,000 coding exons in the human genome • Represents approximately 30 Mb of the total 6.4Gb diploid human genome (~1.1% of the total) • But they encode the vast majority of information relevant to protein structures CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 16. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics The Exome • The exome is the part of the genome formed by exons, the sequences which when transcribed remain within the mature RNA after introns are removed by RNA splicing • There are ~180-200,000 coding exons in the human genome • Represents approximately 30 Mb of the total 6.4Gb diploid human genome (~1.1% of the total) • But they encode the vast majority of information relevant to protein structures • Because most high penetrance (i.e. Mendelian or nearly so) variation is mediated by non-synonymous, frameshifting and canonical splice variation, exomes are ideal for studying the relationship of such variation to health and disease CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 17. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Beta-Globin Gene Structure STOP START Promoter Exon 1 5’UTR Exon 2 Intron 1 Exon 4 Exon 3 Intron 2 3’UTR Conservation CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 18. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics The standard exome only includes these few Protein-encoding elements STOP START Promoter Exon 1 5’UTR Exon 2 Intron 1 Exon 4 Exon 3 Intron 2 3’UTR Conservation CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 19. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics STOP START Promoter Exon 1 5’UTR Exon 2 Intron 1 Exon 4 Exon 3 Intron 2 3’UTR Conservation The other coding and non-coding regions of importance are generally not included CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 20. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics WES: pluses • Therefore analysing exomes compared with genomes involves a huge reduction in complexity • A reduction in complexity equates to a very significant reduction in sequencing costs compared with whole genome sequencing (~15% the cost) • It takes a much shorter time to generate the data - you can generate 1,000 exomes in the time it takes to do 67 whole genomes • The computing time for exomes is about 1/15th that for a whole genome CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 21. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics WES: pluses • Therefore analysing exomes compared with genomes involves a huge reduction in complexity • A reduction in complexity equates to a very significant reduction in sequencing costs compared with whole genome sequencing (~15% the cost) • It takes a much shorter time to generate the data - you can generate 1,000 exomes in the time it takes to do 67 whole genomes • The computing time for exomes is about 1/15th that for a whole genome • Provides a focus on just the regions where clinical molecular geneticists provide the best interpretation, therefore the medicolegal issues are somewhat reduced • It has been called the ‘sweet spot’ in genomics where a lot can be achieved for moderate cost CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 22. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics WES: minuses • Doesn’t address variants in non-coding regions or even non-coding exons • It doesn’t look at regions involved in transcriptional regulation • It has limited ability at present to resolve copy number variants by looking at read depth • It has virtually no useful role at present in looking at balanced structural alterations such as large inversions or translocations. • Can’t detect UPD • With short reads, Fragile X and other trinucleotide repeats are not able to be characterised Are the pluses sufficient to out-weigh the minuses for a diagnostic lab? CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 23. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Applications of WES • There are two predominant applications of WES - gene discovery in the research context - mutation identification for patient diagnosis Mendelian gene discovery: • 497 publications reporting 457 new disease genes since November 2009 • The rate of gene discovery is increasing and is approaching 1 new Mendelian disease gene per day
  • 24. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics WES is Accelerating Mendelian Gene Discovery Number of Mendelian Disease Genes Published per Quarter 90 80 70 60 50 40 Number Power (Number) 30 20 10 0 CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 25. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Gene identification is becoming routine 90 80 70 60 50 Number 40 Mean IF Power (Mean IF) 30 20 10 0 CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 26. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Success of Exome Seq for Gene Discovery • Reviewed 24 Mendelian disorders studied in Nijmegen. • Research based patient cohorts who had a syndromic diagnosis • Frequently multiple families were available for analysis from different ethnic populations. - 6/10 dominant disorders were identified - 8/14 recessive disorders identified • Overall 58% success in research studies for gene identification purposes. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 27. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Factors Influencing Success in Gene Discovery • That the condition is truly a genetic disorder and its mode of inheritance is predictable (e.g. de novo dominant v. recessive) • Careful and correct clinical/laboratory phenotyping is ESSENTIAL • Have sufficient numbers of affected and unaffected individuals available from several families • Pre-existing linkage or homozygosity mapping information is useful • The gene is targeted by the exome selection kit CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 28. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Performance of WES for Diagnosis? • Gilissen et al 2012 modelled the sensitivity of WES for known disease causing variants. • Evaluated the sequence coverage of 50 exomes for 37,424 nonsynonymous variants in Human Gene Mutation Database that don’t overlap with known SNPs - 2,128 (5.7%) were not covered by any reads - 30,239 (81%) had >10 reads • Suggests that WES mutation sensitivities may top out at about 80%, and therefore WES is best considered as a good screening test • Improvements in depth of sequencing are needed. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 29. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Performance of WES for Targeted Diagnosis • Eleven published studies using the whole exome sequencing approach to target a defined set of genes (>5 unrelated probands, unknown case mutation status) CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 30. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Performance of WES for Targeted Diagnosis • Eleven published studies using the whole exome sequencing approach to target a set of genes. (>5 unrelated probands, unknown case mutation status) PMID Disorder Heterogeneity Cohort Known Novel Genes Mitochondria 10 84 42 7 5 23 20 41 18 163 12 9 450 111 76 9 9 3 48 7 3 3 1 20 1 Mitochondrial complex I deficiency PMID: 23596069 Suspected mitochondrial disorders. >1000 PMID: 22277967 mitochondrial oxidative phosphorylation disease >1000 K&N Sensitivity 12 15 PMID: 22499348 Known 70% 6% 55% 70% 37% 86% 60% 37% 60% 37% 3 11 67% 6% 83% 12% 5 2 7 66% 33% 11% 42% 14% 66% 89% 33% 56% 14% 26 13 Neurosensory disorders PMID: 23226338 Autosomal recessive nonsyndromic hearing loss. 39 PMID: 23661368 Leber congenital amaurosis. 19 Complex Neurological Disorders PMID: 23169490 Meckel-Gruber syndrome in Arabs 10 PMID: 23352163 Multipex families with autism. 70 Others PMID: 23035047 PMID: 22662265 PMID: 22492991 Neonates in NICU Pre-screened MODY. Prescreened Congenital disorders of glycosylation I PMID: 23054246 Prescreened Familial Hypercholesterolaemia. PMID: 23409019 non-BRCA1/BRCA2 familial breast cancer 20 9 CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 31. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Performance of WES for Targeted Diagnosis • Eleven published studies using the whole exome sequencing approach to target a set of genes. (Minimum of 6 unrelated probands) PMID Disorder Heterogeneity Cohort Known Novel Genes Mitochondria 10 84 42 7 5 23 20 41 18 163 12 9 111 76 9 3 48 7 3 1 20 1 Mitochondrial complex I deficiency PMID: 23596069 Suspected mitochondrial disorders. >1000 PMID: 22277967 mitochondrial oxidative phosphorylation disease >1000 K&N Sensitivity 12 15 PMID: 22499348 Known 70% 6% 55% 70% 37% 86% 60% 37% 60% 37% 3 11 67% 6% 83% 12% 5 2 7 33% 11% 42% 14% 89% 33% 56% 14% 26 13 Neurosensory disorders PMID: 23226338 Autosomal recessive nonsyndromic hearing loss. 39 PMID: 23661368 Leber congenital amaurosis. 19 Complex Neurological Disorders PMID: 23169490 Meckel-Gruber syndrome in Arabs 10 PMID: 23352163 Multipex families with autism. 70 Others PMID: 22662265 PMID: 22492991 Pre-screened MODY. Prescreened Congenital disorders of glycosylation I PMID: 23054246 Prescreened Familial Hypercholesterolaemia. PMID: 23409019 non-BRCA1/BRCA2 familial breast cancer 20 9 • Average sensitivity of mutation detection was 39% for known genes, rising to 54% for known plus novel genes (medians 42% and 60% respectively)
  • 32. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Targeted Exome Sequencing • Exome Seq now has two forms, Targeted and Whole exome sequencing • Illumina markets a clinical exome product (TruSight Exome) which targets the 2761 genes in HGMD databases with known clinical effect on the date of design. • Little published data but appears a good solution for common disease genes • Lacks targets in some clinically significant genes - Erf Variable suture craniosynostosis - TCF12 Multisuture craniosynostosis - SLC29A3 Histiocytosis/Lymphadenopathy + syndrome . CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 33. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Reverse Phenotyping • WES has a role in correcting phenotypic classification, so called reverse phenotyping . Reverse Phenotyping PMID: 22378277 PMID: 22730194 PMID: 22823409 PMID: 22901280 PMID: 23468869 PMID: 23483706 FSHD2 to LGMD2A Charcot-Marie-Tooth disease. ASPM in apparent X-linked microcephalic intellectual deficit. atypical episodic muscle weakness. rett syndrome exome sequencing. ATL1 Blurs Autosomal Dominant Inheritance of Spastic Paraplegia. Leidenroth A, et al. Choi BO, et al. Ariani F et al. Hanchard NA, et al. Grillo E, et al. Varga RE, et al. PMID: 23610050 PMID: 23652424 Bartsocas-Papas syndrome. PROP1 Deficiency: Clinical Impact of WES X-linked adrenoleukodystrophy mimicking recessive hereditary spastic paraplegia. A Novel OPA3 Mutation Revealed by Exome Sequencing Gripp KW, et al. Wassner AJ, et al. Eur J Hum Genet. 2012 Sep;20(9):999-1003 Hum Mutat. 2012 Nov;33(11):1610-5 Clin Genet. 2013 Mar;83(3):288-90 Clin Genet. 2013 May;83(5):457-61 PLoS One. 2013;8(2):e56599 Hum Mutat. 2013 Jun;34(6):860-3 Am J Med Genet A. 2013 May;161A(5):105863 Horm Res Paediatr. 2013 May 3 Zhan ZX, et al. Arif B, et al. Eur J Med Genet. 2013 May 9 JAMA Neurol. 2013 Jun 1;70(6):783-7 PMID: 23664929 PMID: 23700088 CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 34. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Reverse Phenotyping • WES has a role in correcting phenotypic classification, so called reverse phenotyping . Reverse Phenotyping PMID: 22378277 PMID: 22730194 PMID: 22823409 PMID: 22901280 PMID: 23468869 PMID: 23483706 FSHD2 to LGMD2A Charcot-Marie-Tooth disease. ASPM in apparent X-linked microcephalic intellectual deficit. atypical episodic muscle weakness. rett syndrome exome sequencing. ATL1 Blurs Autosomal Dominant Inheritance of Spastic Paraplegia. Leidenroth A, et al. Choi BO, et al. Ariani F et al. Hanchard NA, et al. Grillo E, et al. Varga RE, et al. PMID: 23610050 PMID: 23652424 Bartsocas-Papas syndrome. PROP1 Deficiency: Clinical Impact of WES X-linked adrenoleukodystrophy mimicking recessive hereditary spastic paraplegia. A Novel OPA3 Mutation Revealed by Exome Sequencing Gripp KW, et al. Wassner AJ, et al. Eur J Hum Genet. 2012 Sep;20(9):999-1003 Hum Mutat. 2012 Nov;33(11):1610-5 Clin Genet. 2013 Mar;83(3):288-90 Clin Genet. 2013 May;83(5):457-61 PLoS One. 2013;8(2):e56599 Hum Mutat. 2013 Jun;34(6):860-3 Am J Med Genet A. 2013 May;161A(5):105863 Horm Res Paediatr. 2013 May 3 Zhan ZX, et al. Arif B, et al. Eur J Med Genet. 2013 May 9 JAMA Neurol. 2013 Jun 1;70(6):783-7 PMID: 23664929 PMID: 23700088 • Raises the possibility of whether an unbiased exome approach may yield more correct patient diagnoses than clinical genetics. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 35. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Performance of WES in the Diagnosis of Unknown/Complex Disorders Najmabadi et al Dixon-Salazar et Need et al Nature Sept 2011 Sci Trans Med June 2012 J Med Genet June 2012 136 ID probands from consanguineous families 118 ID probands from consanguineous families 12 parent-child unselected trios Studied homozygous regions Studied homozygous regions Studied de novo mutations 26 of 136 (19%) diagnoses 32 of 118 (27%) diagnoses 6 of 12 (50%) diagnoses 2 possible further diagnoses CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 36. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Performance of WES for Diagnosis • Baylor College of Medicine experience: BCM recently published results of 250 exomes predominantly children with neurological disorders, 62 of 250 (25%) had a genetic cause of their disorder identified by WES In 4% the diagnosis was revised base don the exome findings About 3% end up with better management 4% total personal benefit Only 1% get a treatment and major benefit CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 37. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Performance of WES for Diagnosis • Baylor College of Medicine experience: BCM recently published results of 250 exomes predominatly children with neurological disorders, 62 of 250 (25%) had a genetic cause of their disorder identified by WES In 4% the diagnosis was revised base don the exome findings About 3% end up with better management Only 1% get a treatment and major benefit • Not every exome sequencing study will work, but is vast improvement over previous experience. • Baylor College of Medicine currently charges $US7,000 - 9,000 for a family exome study, so approximately $200,000 per case showing management improvement CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 38. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Familial Trios for de novo mutations de Ligt et al Rauch et al Yang et al N Eng J Med Oct 2012 Lancet Nov 2012 N Eng J Med Oct 2013 100 parent-child trios with MR 45 cases parent-child trios 33 AD cases 9 XL cases Targeted de novo mutations Targeted de novo mutations Targeted de novo and inherited disorders 12 de novo mutations in genes known to cause MR 16 de novo mutations in genes known to cause MR 83% AD were de novo 40% XL were de novo Total 16 of 100 (16%) ‘de novo’ diagnoses 6 /45 in novel genes (48%) ‘de novo’ diagnoses CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 39. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Research/Diagnosis Boundaries in WES • In the early years of genomics practice in diagnostic labs it is to be expected that frequently a project that starts out as pure diagnosis will merge into a research project depending on whether or not a pathogenic mutation in a known gene is discovered. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 40. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Research/Diagnosis Boundaries in WES • In the early years of genomics practice in diagnostic labs it is to be expected that frequently a project that starts out as pure diagnosis will merge into a research project depending on whether or not a pathogenic mutation in a known gene is discovered. • Eurogentest best practice committee considered this situation and has suggested the following boundaries: CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 41. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Research/Diagnosis Boundaries in WES • In the early years of genomics practice in diagnostic labs it is to be expected that frequently a project that starts out as pure diagnosis will merge into a research project depending on whether or not a pathogenic mutation in a known gene is discovered. • Eurogentest best practice committee considered this situation and has suggested the following boundaries: - Diagnostic clinical molecular genetics reporting is considered to be based on reporting existing EVIDENCE of causality between a detected variant and a disease state. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 42. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Research/Diagnosis Boundaries in WES • In the early years of genomics practice in diagnostic labs it is to be expected that frequently a project that starts out as pure diagnosis will merge into a research project depending on whether or not a pathogenic mutation in a known gene is discovered. • Eurogentest best practice committee considered this situation and has suggested the following boundaries - Diagnostic clinical molecular genetics reporting is considered to be based on reporting existing EVIDENCE of causality between a detected variant and a disease state. - Research genetics is based on a HYPOTHESIS of an association between a variant and a phenotype, condition or disorder. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 43. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Research/Diagnosis Boundaries in WES • In the early years of genomics practice in diagnostic labs it is to be expected that frequently a project that starts out as pure diagnosis will merge into a research project depending on whether or not a pathogenic mutation in a known gene is discovered. • Eurogentest best practice committee considered this situation and has suggested the following boundaries - Diagnostic clinical molecular genetics reporting is considered to be based on reporting existing EVIDENCE of causality between a detected variant and a disease state. - Research genetics is based on a HYPOTHESIS of an association between a variant and a phenotype, condition or disorder. • Diagnostic reporting therefore stops where there is no prior evidence, but a diagnostic report may include a recommendation for further research between an observation and a disease state. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 44. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics New Concept - Diagnostic Yield • Eurogentest best practice meeting Feb 2013 endorsed the following concepts as performance characteristics to evaluate WES diagnostic testing. - diagnostic yield: the number of patients who receive a molecular confirmation of a given clinical diagnosis. It is the likelihood that a test, which can include multiple genes, will provide the information needed to establish a genetic diagnosis CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 45. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics NGS Diagnostic Yield • Eurogentest best practice meeting Feb 2013 endorsed the following concepts as performance characteristics to evaluate WES diagnostic testing. - diagnostic yield: the number of patients who receive a molecular confirmation of a given clinical diagnosis. It is the likelihood that a test, which can include multiple genes, will provide the information needed to establish a genetic diagnosis - In order to justify changing a test from Sanger based to NGS based sequencing it should result in a diagnostic yield that at least matches sequential gene testing using Sanger sequencing. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 46. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics NGS Diagnostic Yield • Eurogentest best practice meeting Feb 2013 endorsed the following concepts as performance characteristics to evaluate WES diagnostic testing. - diagnostic yield: the number of patients who receive a molecular confirmation of a given clinical diagnosis. It is the likelihood that a test, which can include multiple genes, will provide the information needed to establish a genetic diagnosis - In order to justify changing a test from Sanger based to NGS based sequencing it should result in a diagnostic yield that at least matches sequential gene testing using Sanger sequencing. - NGS based analysis of a large gene set or exome/genome will not cover all targeted bases as well as Sanger sequencing but will result in more diagnoses, particularly in diseases with extreme locus heterogeneity such as deafness, intellectual disability, thoracic aneurysms and many more CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 47. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics NGS Diagnostic Yield Current Investigation of non syndromic ID Cytogenetics ~10-15% Chromosomal Microarray ~ 5 -15% Fragile X ~1% Metabolic/specific genetic tests ~5% Overall 20-30% diagnostic sensitivity CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 48. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics NGS Diagnostic Yield Current Investigation of non syndromic ID Genomic Diagnosis of nsID Cytogenetics ~10-15% Chromosomal Microarray ~15-30% Chromosomal Microarray ~ 5 -15% Fragile X ~1% Fragile X ~1% Metabolic/specific genetic tests ~5% Overall 20-30% diagnostic sensitivity NGS Trios ~19-50% Overall >50-60% diagnostic sensitivity CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 49. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics NGS Core Disease List • To guarantee uniform and transparent molecular testing between clinical genetic laboratories it is recommended each lab defines and maintain a ‘core disease gene’ list for genetic diseases. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 50. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics NGS Core Disease List • To guarantee uniform and transparent molecular testing between clinical genetic laboratories it is recommended each lab defines and maintain a ‘core disease gene’ list for genetic diseases. - Genes on this list are considered to be ‘disease essential’ as defined by a team of medical and genetic experts. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 51. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics NGS Core Disease List • To guarantee uniform and transparent molecular testing between clinical genetic laboratories it is recommended each lab defines and maintain a ‘core disease gene’ list for genetic diseases. - Genes on this list are considered to be ‘disease essential’ as defined by a team of medical and genetic experts. - Mutation frequencies detected within these ‘core disease genes’ are significant for that particular disorder and warrant a sequencing quality that matches current practice (i.e. high sensitivity and specificity). CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 52. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics NGS Core Disease List • To guarantee uniform and transparent molecular testing between clinical genetic laboratories it is recommended each lab defines and maintain a ‘core disease gene’ list for genetic diseases. - Genes on this list are considered to be ‘disease essential’ as defined by a team of medical and genetic experts. - Mutation frequencies detected within these ‘core disease genes’ are significant for that particular disorder and warrant a sequencing quality that matches current practice (i.e. high sensitivity and specificity). - It is required that all genes mentioned on this list are tested at high quality and that this specific quality requirement is clearly indicated in the final report. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 53. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics An example of a NGS Core Disease List Core Genes BRCA1 BRCA2 Offer NGS, with Sanger pick-up of any region not covered to diagnostic standard as well as MLPA CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 54. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics NGS Core Disease List Core Genes BRCA1 BRCA2 Non-Core Genes ATM TP53 CHEK2 PTEN CDH1 PALB2 Offer NGS, with Sanger pick-up of any region not covered to diagnostic standard as well as MLPA Offer NGS and exon chromosomal microarray but with only a guarantee to sequence each gene to a screening standard CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 55. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics The Ideal Pipeline • Ideally we would like a diagnostic pipeline which could identify all classes of mutation associated with human genetic disease • It would need to be capable of: - the detection of all DNA sequence mutations - exon resolution copy number mutation detection through bioinformatic processing of read-stack data - balanced structural mutation detection by length defined mate pairs - identifying non-human DNA inserted into a gene, by de novo assembly - ability to detect UPD by analysis of minor allele frequency usage - characterising changes in methylation patterns by sequencing captured methylated DNA - detecting changes in levels of expression CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA
  • 56. CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA SEALS Genetics Whole Genome Sequencing • The solution that would best fit these needs will clearly be whole genome sequencing • It would need to be capable of: - the detection of DNA sequence mutations , 5-10-% better exon coverage than exome approaches - exon resolution copy number mutation detection bioinformatic processing of read-stack data - balanced structural mutation detection by direct detection or via length defined mate pairs - identifying non-human DNA inserted into a gene, by de novo assembly - ability to detect UPD by analysis of minor allele frequency usage - characterising changes in methylation patterns by recognising methylated bases directly or by sequencing directly captured methylated DNA CCCAGATGCCCTGTTCCAGGAGGACAGCTACAAGAAACACCTGAAGCATCACTGTAACAAGTATGTTATTAGAGGGTGGACCTGGAGAGCTTAATTCCCTTTTTATTCTTTAAAAAATACATGCAGCCGGCCCTTCACGTCTGCAGATGCAGAACTCGCAGATTTGGAGGGTCAACTGAGGGACCTGAGCATCTGCGGATCTTGGTGTCTGAGGGGGGTCCTGGAACCATACTCCCGCGGATATGGAGGGACAGCTCTG TTATTAAGACTTTTAAATGGTATAGTTATTGCCTTTGCACAGCCTTATCATTTTTCTTGAAATGTGGTGTCAAGTTGCAGGAGAGCGTACCTTTAGGTGACTGATTATTTTTTAACATGGTAAGATACACAACACAACGTTTACCATTTTTACCATTTATAAGTGAACAATTCATTGGCATTAATTACACTCACAATGCTGTATACTCACTATCTGTACCTGAAATGTTTCCATCTTCCCAAATATAAACACTGTATCAATTAAACA